# Expert Consensus on Criteria for the Automated Assessment of Laparoscopic Camera Navigation

arXiv: https://arxiv.org/abs/2606.23131 · HTML: https://mlsanity.com/paper/2606.23131/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 50 references that are in the map.
- First posted on arXiv 22 Jun 2026.

## Builds on (most cited first, 15 of 15)

- [ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM](https://mlsanity.com/paper/2007.11898/) (2020)
- [EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos](https://mlsanity.com/paper/1602.03012/) (2016)
- [Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos](https://mlsanity.com/paper/2109.03223/) (2021)
- [AutoLaparo: A New Dataset of Integrated Multi-tasks for Image-guided Surgical Automation in Laparoscopic Hysterectomy](https://mlsanity.com/paper/2208.02049/) (2022)
- [LoViT: Long Video Transformer for Surgical Phase Recognition](https://mlsanity.com/paper/2305.08989/) (2023)
- [Learning How To Robustly Estimate Camera Pose in Endoscopic Videos](https://mlsanity.com/paper/2304.08023/) (2023)
- [EndoGSLAM: Real-Time Dense Reconstruction and Tracking in Endoscopic Surgeries using Gaussian Splatting](https://mlsanity.com/paper/2403.15124/) (2024)
- [A deep learning framework for quality assessment and restoration in video endoscopy](https://mlsanity.com/paper/1904.07073/) (2019)
- [A spatio-temporal network for video semantic segmentation in surgical videos](https://mlsanity.com/paper/2306.11052/) (2023)
- [CholecTrack20: A Multi-Perspective Tracking Dataset for Surgical Tools](https://mlsanity.com/paper/2312.07352/) (2023)
- [CudaSIFT-SLAM: multiple-map visual SLAM for full procedure mapping in real human endoscopy](https://mlsanity.com/paper/2405.16932/) (2024)
- [Adaptive specular reflection detection and inpainting in colonoscopy video frames](https://mlsanity.com/paper/1802.08402/) (2018)
- [Conformal forecasting for surgical instrument trajectory](https://mlsanity.com/paper/2503.04191/) (2025)
- [A Neural Network based Framework for Effective Laparoscopic Video Quality Assessment](https://mlsanity.com/paper/2202.04517/) (2022)
- [BDIS-SLAM: A lightweight CPU-based dense stereo SLAM for surgery](https://mlsanity.com/paper/2312.15679/) (2023)

## Abstract (arXiv)

Background: Laparoscopic camera navigation (LCN) is a critical skill, yet its current assessment typically relies on manual rating systems which are time-consuming and difficult to scale. Automated feedback could significantly enhance surgical training by providing immediate, standardized metrics. This study aims to define, clinically evaluate the relevance, and establish the technical readiness of a set of approaches for LCN assessment. Methods: We developed a detailed taxonomy of 14 key aspects of camera navigation, categorized into Framing & Composition, Visibility & Clarity, Orientation & Stability, Motion & Dynamics, and Safety & Awareness. For each aspect, we assessed the technological readiness of automated measurement based on the current state of the art (SoTA) in computer vision (CV). To establish clinical relevance, we designed a survey for practicing laparoscopic surgeons to rate the importance of each aspect on a 5-point Likert scale and to select the five most critical skills. Results: 23 surgeons participated in the survey. Foundational aspects like Field of View, Focus and Centering were rated as most important by surgeons. We present a "Clinical Importance vs. CV Technological Readiness" matrix, identifying high-priority targets for development--aspects that are both clinically crucial and technologically ready to measure. Conclusion: This work establishes a foundational framework for quantifying LCN skills. By aligning surgeon priorities with CV capabilities, we provide a clear roadmap for automatic skill assessment. This foundation enables the development of AI-driven assistance tools that can accelerate the learning curve for surgical assistants and potentially improve surgical safety and efficiency.